Organizational Analytics – Innovative or Invasive?

As we spend more of our life in a digital world, we leave a richer and more complete trail of digital breadcrumbs behind us for the analytics algorithms to scoop up, each crumb telling something else about us. While this is a veritable candy shop of goodies for information scientists, we do have to ask ourselves the question “Just because we can (poke our nose into the most intimate details of peoples lives), should we?”.

“When does social analytics move from being innovative to invasive?”

Organizational analytics is one example where social analytics has the potential to deliver hugely valuable insights, both to the individuals within the organization and to the organization as a whole.

To the individual it can let them know:

  • What topics are trending that they might care about?
  • Who else is working in their area (with whom they might collaborate)?
  • Who might be able to help them close this deal or review their paper?
  • How effective is their time mgmt, should they re-prioritize items?
  • Who are the most influential people that could help move my work forward?

A great set of questions to be able to ask, and so the big question becomes: “Am I willing to accept these benefits if it also means it may come with some negative side-effects, such as my privacy?”

For an organization it can let them know:

  • Is the organization happy?
  • Is it overworked?
  • Which teams appear most active?
  • Does this align to productivity?
  • Which processes are taking up most of people’s time?
  • Could things be done differently to improve productivity?

Again, really great stuff for an organization to know. { as long as the raw data doesn’t get abused to ask more invasive questions }

It’s a tricky ol’ question, for which I don’t claim to have the answer. I know on a personal level I would probably be willing to give up a lot of my data if it meant I benefit from some of the intelligence derived from that data. However it would all depend on my ability to be able to control what information is shared and how that information could ultimately be used. I feel that’s the key — access and privacy controls. What I don’t want (which is frequently the case today) is that my information ends up going God knows where and is used by God knows who to do God knows what and that ain’t a good situation!

So,  what sort of protections need to be in place around our data (content & interactions), because clearly the lid is off Pandora’s box and nothing is going to put it back on again.

2 Comments to “Organizational Analytics – Innovative or Invasive?”

  1. As someone who has a very heavy metric tracked job here is my 2c on it.

    First, it doesn’t matter what metric you attempt to capture, nearly always someone will have an issue with it. Even if that metric portrays them in a positive light, or highlights an area you can help to improve that engineers skills/role.

    Also it is important to look beyond the finished results.

    Any metric that the end user realizes they are being tracked on in relation to performance, they will work towards hitting that metric rather then the purpose of what the metric is supposed to convey.

    The metric also needs to either be invisible, or you have to be able to drill down to causes of the results.

    Example. “95% of your customers are happy”. That is meaningless to me.


    • I couldn’t agree more re: the transparency / drill-down point. I am also not convinced on the usefulness of any single personal performance metric. I do however believe that a range of metrics can provide guidance to:

      • The Organization: For example; who in my organization is a critical hub in the network (people always go to them for help with X).
      • The Individual: For example; what organizations are working on a related problem space (related topic trends).

      The key is to focus on measuring things which directly improve organizational performance, such as reducing the time people spend looking for information by 90% OR reducing the amount of duplication by 60%.


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